🔹Neuroexplicit Models of Language, Vision, and Action
🔹Machine Learning and Parkinson’s Disease
🔹Recurrent Neural Network Models of Neural Dynamics
🔹Machine learning for predicting disease trajectories in dementia using neuroimaging, genetics, and behavioral data
🔹Developing a multiscale model of Dravet syndrome
🔹Computer Vision for Robotics
🔹Artificial Intelligence and Formal Methods
🔹Machine Learning for Adaptive Data Analysis and Differential Privacy

🔹Multiple Studentships in Computer Vision, Deep Learning, ML, AI, and related areas
🔹Physics-Informed Robot Learning, Research in Robotics, Reinforcement Learning, Neural PDEs, Deformable Object Manipulation, Human-centered Robot Manipulation
🔹Optimization/AutoML/Automatic Algorithm Configuration
Interactive Causal Explanations for Patient-centric Personalised Health (Focus on causal inference, healthcare, explainable AI)
🔹Machine Learning for Quantitative Finance: derivatives pricing, portfolio optimization, and advanced ML techniques
🔹Mathematical Neuroscience: Focus on mathematical modelling, neural processing, and dynamical systems theory
🔹Neuroscience Scholarships: For experimentalists and computational candidates
🔹Position in Computer Science with a Focus on Cybersecurity
🔹Semantic Perception: Adaptive Sensor Fusion for Autonomous Driving in Extreme Weather
🔹Machine Learning for Prostate Cancer : AI models integrating histology, single-cell RNA sequencing, and spatial omics for metastasis prediction.
🔹Adaptive Data Analysis, Differential Privacy, and ML+Databases
🔹Deep Learning for Limited Labeled Data, Geometry of Embedding Spaces, and Multi-Modality Alignment.
🔹Theoretical Statistics, Machine Learning, Optimization, Signal Processing, Computer Science, and Applied Mathematics.
🔹 Human Motor Neurophysiology: Multiscale Sensorimotor Communication Research